CN112880662B - Method and system for generating morphological map of field geology and landform - Google Patents
Method and system for generating morphological map of field geology and landform Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000000877 morphologic effect Effects 0.000 title claims abstract description 19
- 230000007613 environmental effect Effects 0.000 claims abstract description 111
- 238000006243 chemical reaction Methods 0.000 claims abstract description 7
- 230000009466 transformation Effects 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 15
- 230000000875 corresponding effect Effects 0.000 claims description 12
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 4
- 238000012549 training Methods 0.000 claims description 4
- 230000001131 transforming effect Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000002596 correlated effect Effects 0.000 claims description 3
- 238000012876 topography Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract description 2
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
- G06T11/206—Drawing of charts or graphs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/60—Editing figures and text; Combining figures or text
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30184—Infrastructure
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30192—Weather; Meteorology
Abstract
The invention discloses a method and a system for generating a morphological map of field geology and topography, which relate to the technical field of map drawing and have the technical scheme that: determining a calibration area of a corresponding calibration node according to the preset calibration distance and the positioning information; performing data conversion on the hyperspectral image data, and then constructing a calibration map; predicting to obtain an environmental condition data sequence; expanding to obtain an environmental condition distribution set sequence corresponding to the calibration area; storing the environmental condition distribution set sequence in a storage file; marking and displaying the running track line on a calibration map; and matching and reading the storage file by inputting the matching information. According to the method, after hyperspectral image data in a calibration area are obtained through a hyperspectral remote sensing technology, a calibration map is initially established, and the coverage area is large; the environmental condition distribution set sequence of the calibration area on the time axis is determined by predicting the calibration nodes from the time dimension and the area dimension, the data is comprehensive and accurate, and the method has wide application prospects in the aspects of geological exploration, outdoor exercises, travel and the like.
Description
Technical Field
The invention relates to the technical field of map drawing, in particular to a method and a system for generating a morphological map of field geology and landform.
Background
The global positioning system (GPS, globalPositioningSystem) has been widely used in various fields, most vehicles and intelligent terminals can provide accurate positioning information, traffic information and urban road information for users in real time, and reasonable routes for users to reach the purpose can be set in real time according to the requirements of the users, so that the system is widely popular for the users.
The field work is a phenomenon existing in geological exploration for a long time, and the field work position is usually in a region with complex topography, such as mountain areas, jungle, gobi, desert and the like. In actual work, an exploration person manually inputs and draws a geological landform map of a passing region through a drawing or an intelligent terminal, so that the situation that the working efficiency is low, the error is large, the data is inaccurate and the like exists, and the geological landform map drawing region is limited; in addition, the field environment is complex and changeable, and the geological landform map drawn by the prior art has no great reference significance for secondary reference.
Therefore, how to research and design a method and a system for generating an intelligent field geological landform map with comprehensive data and high accuracy is an urgent problem to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a method and a system for generating a morphological map of field geology and geomorphic, and the method and the system have wide application prospects in geological exploration and outdoor exercises.
The technical aim of the invention is realized by the following technical scheme:
in a first aspect, a method for generating a morphological map of field geology is provided, which includes the following steps:
s101: positioning information of the calibration nodes and time information of running to the calibration nodes are obtained, and calibration areas of the corresponding calibration nodes are determined according to preset calibration distances and the positioning information;
s102: the hyperspectral image data of the calibration area are synchronously acquired through hyperspectral remote sensing, and a calibration map is constructed after the hyperspectral image data are subjected to data conversion;
s103: according to the time information, synchronously acquiring environmental condition data at a calibration node and meteorological data in the current day, and inputting the meteorological data and the environmental condition data into an environmental data prediction model for prediction to obtain an environmental condition data sequence;
s104: inputting the environmental condition data sequence and the hyperspectral image data into a prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area;
s105: generating a matching identifier according to the calibration area, the environmental condition data and the time information, establishing a storage file by taking the matching identifier as a file name, and storing the environmental condition distribution set sequence in the storage file;
s106: sequentially connecting adjacent calibration nodes to form a running track line, and marking and displaying the running track line on a calibration map;
s107: and matching and reading the storage file by inputting at least one matching information of positioning, environmental conditions and time.
Furthermore, the positioning information and the time information are respectively obtained in real time through a GPS (global positioning system) positioner and a timer which are assembled on the target user.
Further, the determination of the calibration area is specifically:
determining a circular calibration area by taking a preset calibration distance as a radius and a calibration node as a circle center;
or determining a square calibration area by taking the preset calibration distance as one half side length and the calibration node as a diagonal intersection point.
Further, the calibration map includes geological information, geomorphic information, and morphological information.
Further, the specific process of predicting the environmental condition data sequence is as follows:
intercepting real-time meteorological data of the calibration node from the meteorological data in the current day according to the time information;
comparing and analyzing the real-time meteorological data with other moment meteorological data in the current day to obtain analysis transformation parameters;
and transforming the environmental condition data at the calibration nodes according to the analysis transformation parameters to obtain an environmental condition data sequence which is continuously distributed on the time axis of the calibration nodes in the same day.
Further, the environmental condition data comprise temperature data, humidity data and wind power data which are respectively acquired in real time through a temperature sensor, a humidity sensor and a wind sensor which are assembled on a target user.
Further, the expanding process of the environmental condition distribution set sequence specifically comprises the following steps:
according to the positioning information, intercepting hyperspectral data of a calibration node from hyperspectral image data;
the hyperspectral data and the environmental condition data of the calibration nodes are simultaneously input into a prediction expansion model for training to obtain equivalent transformation parameters;
the prediction expansion model predicts and expands the hyperspectral image data according to the equivalent transformation parameters and then outputs an environmental condition data set of which all positions in the calibration area are at the same time node;
and sequentially inputting the environmental condition data sequences of the calibration nodes into a prediction expansion model for processing to obtain an environmental condition distribution set sequence of all positions in the calibration area, wherein the environmental condition distribution set sequence is continuously distributed on a time axis in the same day.
Further, the establishing process of the storage file specifically includes:
respectively establishing a first identifier, a second identifier and a third identifier according to the calibration area, the environmental condition data and the time information, and fusing the first identifier, the second identifier and the third identifier into an identification character string as a file name of a storage file after being related in a triangular chain;
establishing a plurality of storage units in a storage file, dividing time information into a plurality of continuous time period information according to a time axis in the same day, and respectively taking the plurality of time period information as unit names of different storage units;
the environmental condition distribution sets in the sequence of environmental condition distribution sets are stored in different storage units, respectively.
Further, the forming process of the driving track line specifically includes:
sequentially connecting a plurality of calibration nodes according to the sequence of the time information;
the line distance between the calibration nodes is positively correlated with the preset calibration distance;
the preset calibration distance is obtained by any one of manual input, calculation according to the running time and the running speed and preset.
In a second aspect, a system for generating a morphological map of field geology is provided, comprising:
the calibration module is used for acquiring positioning information of the calibration nodes and time information of driving to the calibration nodes, and determining calibration areas of the corresponding calibration nodes according to preset calibration distances and positioning information;
the data acquisition module is used for synchronously acquiring hyperspectral image data of the calibration area through hyperspectral remote sensing, and constructing a calibration map after carrying out data conversion on the hyperspectral image data;
the prediction module is used for synchronously acquiring environmental condition data at the calibration node and meteorological data in the current day according to the time information, and inputting the meteorological data and the environmental condition data into the environmental data prediction model for prediction to obtain an environmental condition data sequence;
the expansion module is used for inputting the environmental condition data sequence and the hyperspectral image data into the prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area;
the storage module is used for generating a matching identifier according to the calibration area, the environmental condition data and the time information, establishing a storage file by taking the matching identifier as a file name, and storing the environmental condition distribution set sequence in the storage file;
the marking module is used for sequentially connecting adjacent calibration nodes to form a running track line and marking and displaying the running track line on a calibration map;
and the reading module is used for matching and reading the storage file by inputting at least one matching information of positioning, environmental conditions and time.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method, the calibration nodes are selected in the driving process of the target user, the calibration area of the calibration nodes is determined, hyperspectral image data in the calibration area are synchronously acquired through hyperspectral remote sensing technology, and then a calibration map containing various information such as geological information, landform information and morphological information is initially built, so that the coverage area is large;
2. according to the method, the environmental condition data such as temperature data, humidity data, wind power data and the like of the calibration nodes are obtained in real time through various sensors which synchronously run with a target user, the environmental condition distribution set sequence of the calibration area on a time axis is predicted from the two aspects of time dimension and area dimension by the calibration nodes, and the data are comprehensive and accurate;
3. the method is convenient for a target user to acquire map information around the calibration node in time, can provide comprehensive reference data for the same route of secondary driving or the same route of other people driving, and has wide application prospects in the aspects of geological exploration, outdoor exercises, tourism and the like.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention. In the drawings:
FIG. 1 is a flow chart in an embodiment of the invention;
fig. 2 is a system block diagram in an embodiment of the invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Example 1: a method for generating a morphological map of field geology and topography is shown in figure 1, and is specifically realized by the following steps.
Step one, positioning information of calibration nodes and time information of driving to the calibration nodes are obtained, and calibration areas of the corresponding calibration nodes are determined according to preset calibration distances and the positioning information; the positioning information and the time information are respectively obtained in real time through a GPS (global positioning system) positioner and a timer which are assembled on the target user.
The determination of the calibration area is specifically as follows: determining a circular calibration area by taking a preset calibration distance as a radius and a calibration node as a circle center; or determining a square calibration area by taking the preset calibration distance as one half side length and the calibration node as a diagonal intersection point.
Synchronously acquiring hyperspectral image data of a calibration area through hyperspectral remote sensing, and constructing a calibration map after carrying out data conversion on the hyperspectral image data; the calibration map includes geological information, geomorphic information, and morphological information.
And thirdly, synchronously acquiring environmental condition data at the calibration node and meteorological data in the current day according to the time information, and inputting the meteorological data and the environmental condition data into an environmental data prediction model for prediction to obtain an environmental condition data sequence.
The specific process of predicting the environmental condition data sequence is as follows: intercepting real-time meteorological data of the calibration node from the meteorological data in the current day according to the time information; comparing and analyzing the real-time meteorological data with other moment meteorological data in the current day to obtain analysis transformation parameters; and transforming the environmental condition data at the calibration nodes according to the analysis transformation parameters to obtain an environmental condition data sequence which is continuously distributed on the time axis of the calibration nodes in the same day.
The environmental condition data comprise temperature data, humidity data and wind power data which are respectively acquired in real time through a temperature sensor, a humidity sensor and a wind sensor which are assembled on a target user.
And step four, inputting the environmental condition data sequence and the hyperspectral image data into a prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area.
The expansion process of the environmental condition distribution set sequence specifically comprises the following steps: according to the positioning information, intercepting hyperspectral data of a calibration node from hyperspectral image data; the hyperspectral data and the environmental condition data of the calibration nodes are simultaneously input into a prediction expansion model for training to obtain equivalent transformation parameters; the prediction expansion model predicts and expands the hyperspectral image data according to the equivalent transformation parameters and then outputs an environmental condition data set of which all positions in the calibration area are at the same time node; and sequentially inputting the environmental condition data sequences of the calibration nodes into a prediction expansion model for processing to obtain an environmental condition distribution set sequence of all positions in the calibration area, wherein the environmental condition distribution set sequence is continuously distributed on a time axis in the same day.
And fifthly, generating a matching identifier according to the calibration area, the environmental condition data and the time information, and establishing a storage file by taking the matching identifier as a file name, wherein the environmental condition distribution set sequence is stored in the storage file.
The establishment process of the storage file specifically comprises the following steps: respectively establishing a first identifier, a second identifier and a third identifier according to the calibration area, the environmental condition data and the time information, and fusing the first identifier, the second identifier and the third identifier into an identification character string as a file name of a storage file after being related in a triangular chain; establishing a plurality of storage units in a storage file, dividing time information into a plurality of continuous time period information according to a time axis in the same day, and respectively taking the plurality of time period information as unit names of different storage units; the environmental condition distribution sets in the sequence of environmental condition distribution sets are stored in different storage units, respectively.
And step six, connecting adjacent calibration nodes in sequence to form a running track line, and marking and displaying the running track line on a calibration map. The forming process of the running track line comprises the following steps: sequentially connecting a plurality of calibration nodes according to the sequence of the time information; the line distance between the calibration nodes is positively correlated with the preset calibration distance; the preset calibration distance is obtained by any one of manual input, calculation according to the running time and the running speed and preset.
And seventhly, matching and reading the storage file by inputting at least one matching information of positioning, environmental conditions and time.
After the user inputs one kind of matching information in the positioning, the environmental condition and the time, other information with the association relationship can be read through the matching identification character string. For example, by inputting longitude and latitude information or touching and selecting a positioning place in a calibration area, environmental condition data of the positioning place at different time points can be read.
Example 2: a system for generating a morphological map of field geology and topography is shown in fig. 2, and comprises a calibration module, a data acquisition module, a prediction module, an expansion module, a storage module, a labeling module and a reading module. The calibration module is used for acquiring positioning information of the calibration nodes and time information of driving to the calibration nodes, and determining calibration areas of the corresponding calibration nodes according to preset calibration distances and positioning information. The data acquisition module is used for synchronously acquiring hyperspectral image data of the calibration area through hyperspectral remote sensing, and constructing a calibration map after carrying out data conversion on the hyperspectral image data. The prediction module is used for synchronously acquiring the environmental condition data at the calibration node and the meteorological data in the current day according to the time information, and inputting the meteorological data and the environmental condition data into the environmental data prediction model for prediction to obtain an environmental condition data sequence. The expansion module is used for inputting the environmental condition data sequence and the hyperspectral image data into the prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area. And the storage module is used for generating a matching identifier according to the calibration area, the environmental condition data and the time information, establishing a storage file by taking the matching identifier as a file name, and storing the environmental condition distribution set sequence in the storage file. And the marking module is used for sequentially connecting the adjacent calibration nodes to form a running track line and marking and displaying the running track line on the calibration map. And the reading module is used for matching and reading the storage file by inputting at least one matching information of positioning, environmental conditions and time.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. A method for generating a morphological map of field geology is characterized by comprising the following steps:
s101: positioning information of the calibration nodes and time information of running to the calibration nodes are obtained, and calibration areas of the corresponding calibration nodes are determined according to preset calibration distances and the positioning information;
s102: the hyperspectral image data of the calibration area are synchronously acquired through hyperspectral remote sensing, and a calibration map is constructed after the hyperspectral image data are subjected to data conversion;
s103: according to the time information, synchronously acquiring environmental condition data at a calibration node and meteorological data in the current day, and inputting the meteorological data and the environmental condition data into an environmental data prediction model for prediction to obtain an environmental condition data sequence;
s104: inputting the environmental condition data sequence and the hyperspectral image data into a prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area;
s105: generating a matching identifier according to the calibration area, the environmental condition data and the time information, establishing a storage file by taking the matching identifier as a file name, and storing the environmental condition distribution set sequence in the storage file;
s106: sequentially connecting adjacent calibration nodes to form a running track line, and marking and displaying the running track line on a calibration map;
s107: matching and reading a storage file by inputting at least one matching information of positioning, environmental conditions and time;
the specific process for predicting the environmental condition data sequence comprises the following steps:
intercepting real-time meteorological data of the calibration node from the meteorological data in the current day according to the time information;
comparing and analyzing the real-time meteorological data with other moment meteorological data in the current day to obtain analysis transformation parameters;
transforming the environmental condition data at the calibration nodes according to the analysis transformation parameters to obtain environmental condition data sequences which are continuously distributed on the time axis of the calibration nodes in the same day;
the environmental condition data comprise temperature data, humidity data and wind power data which are respectively acquired in real time through a temperature sensor, a humidity sensor and a wind sensor which are assembled on a target user;
the expansion process of the environmental condition distribution set sequence specifically comprises the following steps:
according to the positioning information, intercepting hyperspectral data of a calibration node from hyperspectral image data;
the hyperspectral data and the environmental condition data of the calibration nodes are simultaneously input into a prediction expansion model for training to obtain equivalent transformation parameters;
the prediction expansion model predicts and expands the hyperspectral image data according to the equivalent transformation parameters and then outputs an environmental condition data set of which all positions in the calibration area are at the same time node;
and sequentially inputting the environmental condition data sequences of the calibration nodes into a prediction expansion model for processing to obtain an environmental condition distribution set sequence of all positions in the calibration area, wherein the environmental condition distribution set sequence is continuously distributed on a time axis in the same day.
2. The method for generating a morphological map of field geology according to claim 1, wherein the positioning information and the time information are obtained in real time respectively by a GPS (global positioning system) positioner and a timer which are assembled on a target user.
3. The method for generating a morphological map of field geology according to claim 1, wherein the determination of the calibration area is specifically:
determining a circular calibration area by taking a preset calibration distance as a radius and a calibration node as a circle center;
or determining a square calibration area by taking the preset calibration distance as one half side length and the calibration node as a diagonal intersection point.
4. The method of claim 1, wherein the calibration map comprises geological information, geomorphic information, and morphological information.
5. The method for generating the morphological map of the field geology of claim 1, wherein the establishing process of the storage file is specifically as follows:
respectively establishing a first identifier, a second identifier and a third identifier according to the calibration area, the environmental condition data and the time information, and fusing the first identifier, the second identifier and the third identifier into an identification character string as a file name of a storage file after being related in a triangular chain;
establishing a plurality of storage units in a storage file, dividing time information into a plurality of continuous time period information according to a time axis in the same day, and respectively taking the plurality of time period information as unit names of different storage units;
the environmental condition distribution sets in the sequence of environmental condition distribution sets are stored in different storage units, respectively.
6. The method for generating a morphological map of field geology according to claim 1, wherein the forming process of the travel track line is specifically as follows:
sequentially connecting a plurality of calibration nodes according to the sequence of the time information;
the line distance between the calibration nodes is positively correlated with the preset calibration distance;
the preset calibration distance is obtained by any one of manual input, calculation according to the running time and the running speed and preset.
7. A system for generating a morphological map of field geology is characterized by comprising:
the calibration module is used for acquiring positioning information of the calibration nodes and time information of driving to the calibration nodes, and determining calibration areas of the corresponding calibration nodes according to preset calibration distances and positioning information;
the data acquisition module is used for synchronously acquiring hyperspectral image data of the calibration area through hyperspectral remote sensing, and constructing a calibration map after carrying out data conversion on the hyperspectral image data;
the prediction module is used for synchronously acquiring environmental condition data at the calibration node and meteorological data in the current day according to the time information, and inputting the meteorological data and the environmental condition data into the environmental data prediction model for prediction to obtain an environmental condition data sequence;
the expansion module is used for inputting the environmental condition data sequence and the hyperspectral image data into the prediction expansion model for expansion to obtain an environmental condition distribution set sequence corresponding to the calibration area;
the storage module is used for generating a matching identifier according to the calibration area, the environmental condition data and the time information, establishing a storage file by taking the matching identifier as a file name, and storing the environmental condition distribution set sequence in the storage file;
the marking module is used for sequentially connecting adjacent calibration nodes to form a running track line and marking and displaying the running track line on a calibration map;
the reading module is used for matching and reading the storage file by inputting at least one matching information of positioning, environmental conditions and time;
the specific process for predicting the environmental condition data sequence comprises the following steps:
intercepting real-time meteorological data of the calibration node from the meteorological data in the current day according to the time information;
comparing and analyzing the real-time meteorological data with other moment meteorological data in the current day to obtain analysis transformation parameters;
transforming the environmental condition data at the calibration nodes according to the analysis transformation parameters to obtain environmental condition data sequences which are continuously distributed on the time axis of the calibration nodes in the same day;
the environmental condition data comprise temperature data, humidity data and wind power data which are respectively acquired in real time through a temperature sensor, a humidity sensor and a wind sensor which are assembled on a target user;
the expansion process of the environmental condition distribution set sequence specifically comprises the following steps:
according to the positioning information, intercepting hyperspectral data of a calibration node from hyperspectral image data;
the hyperspectral data and the environmental condition data of the calibration nodes are simultaneously input into a prediction expansion model for training to obtain equivalent transformation parameters;
the prediction expansion model predicts and expands the hyperspectral image data according to the equivalent transformation parameters and then outputs an environmental condition data set of which all positions in the calibration area are at the same time node;
and sequentially inputting the environmental condition data sequences of the calibration nodes into a prediction expansion model for processing to obtain an environmental condition distribution set sequence of all positions in the calibration area, wherein the environmental condition distribution set sequence is continuously distributed on a time axis in the same day.
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